1. GIS AND CASSAVA IN THE CROP CRISIS CONTROL PROJECT AND THE GREAT LAKES CASSAVA INITIATIVE CHRISTOPHER LEGG GIS CONSULTANT

2. Total and per-capita cassava production in Sub-Saharan Africa (FAO data) East African “Great Lakes” region

3. Per-Capita cassava production in East Africa (data from National sources)

4. The Crop Crisis Control Programme (C3P) was financed by USAID and implemented by CRS and IITA to reduce the impact of CMD on food security in the region. The project had a strong component of GIS to collect, analyse and present data on crop health, food security and agricultural production in the six countries of the East African “Great Lakes” region The Great Lakes Cassava Initiative (GLCI) is financed by the Bill and Melinda Gates Foundation to continue the work started by C3P, and is managed by CRS with participation by IITA and many other partners in the region. A strong emphasis on GPS and GIS continues

5. CASSAVA DISEASE SURVEYS HOUSEHOLD SURVEYS ADMINISTRATIVE BOUNDARIES POPULATION DISTRIBUTION AGRICULTURAL PRODUCTION LAND-USE / LANDCOVER MAPS AND TABLES FOR TARGETING CMD BY DISTRICT FOOD PRODUCTION BY DISTRICT CASSAVA DEPENDENCY BY DISTRICT FARMING HOUSEHOLDS PER DISTRICT TARGET DISTRICTS Extraction of population from grids Interpolation of CMD incidence and severity. Averaging to districts Disaggregation of agricultural production statistics to district using land cover Extrapolation of food security data to unsampled districts Interactive selection of target areas by project staff

6. CASSAVA DISEASE SURVEYS HOUSEHOLD SURVEYS RESISTANT PLANTING MATERIAL SURVEYS FARMER GROUP SURVEYS TARGET DISTRICTS DISTRICT WORK PLANS PROGRESS REPORTS INTERNAL ASSESSMENT Maps from field GPS data Maps and statistics from field data Mapping and comparison with previous data Maps and statistics to illustrate changes in food security

7. GPS locations of CMD survey points in NW Tanzania Interpolation of CMD incidence values using IDW to create grid Extraction of mean CMD incidence values for each administrative unit

8. Time series of CMD Incidence data averaged by district 2000-2007 for Uganda shows striking decrease of areas affected by CMD during this period

9. Routine disease surveys also collect information on cassava varieties planted by farmers, and permit monitoring of the arrival of improved and disease-resistant varieties

10. In addition to plant health surveys, data on household food security was collected from all C3P countries during the project, and will be continued through GLCI Calorific dependence on cassava is a direct indicator of the importance of cassava in the diet, and therefore of the potential impact of CMD on health and livelihoods Combinations of data on food security, agricultural production and disease incidence enable more efficient targeting of remedial and defence measures

11. Highest calorific dependence on cassava is in Uganda and eastern DRC The highest CMD incidence in 2006-2007 is at the northern end of Lake Tanganyika in Burundi and DRC, in western Kenya near Kisumu, and in small parts of central and NW Uganda

12. In order to select primary targets for intervention, districts in each country are ranked according to the incidence of CMD, the number of farming households, and the production of cassava. The combined Ranks determine the primary (orange) and secondary (yellow) targets DISTRICT CAS % CMDCMDfarm_hh cassava prod Rank hh Rank cass Rank cmd Total rank Kigoma Rural35.45758712.522222001115 Geita14.56785089.362904001115 Sengerema29.06759879.162904001115 Magu40.95949800.62904002116 Ilemela52.86931784.762904003117 Muleba37.95746222.081128002218 Karagwe40.44650914.441128001229 Kasulu36.44076409.041128001229 Missungwi15.84530735.962904003129 Biharamulo37.76049126.685680023110 Bukombe33.96547435.769610023110 Ngara13.54240129.0811280022210 Bukoba Rural15.74447282.411280022210 Kibondo32.43949653.2422220021310 Kwimba37.8283779129040031311 Tarime47.53958887.728210013313 Bariadi37.32772432.489610013313 Kahama33.12271386.929610013313 Ukerewe54.21231299.7229040031413 Maswa35.92136528.249610033315 Meatu33.02029785.689610043316 Bunda38.52231071.6130034317

13. Areas in NW Tanzania targeted for intervention based on previous table

14. The most important intervention against the food security impact of CMD is replacement of traditional CMD-susceptible cassava varieties by new resistant varieties. C3P supported the production and dissemination of resistant cassava cuttings at many sites throughout the affected areas. This effort is being greatly expanded in GLCI Regular surveys of available planting material, using GPS, enable matching of requirements (CMD incidence, cassava dependence) with supply of cuttings

15. In Uganda, resistant cassava cuttings were available in most affected districts, except in the far north-west

16. In Tanzania, the largest concentrations of resistant cuttings were in areas not seriously affected by CMD. This resulted in re- organisation of cuttings production

17. A new and potentially devastating cassava disease, Cassava Brown Streak Disease (CSBD) has emerged in the region recently, and will be combated in parallel with CMD

18. Incidence of Cassava Brown Streak Disease (CBSD) in East Africa in early 2007

19. GLCI aims to be innovative in data collection and transmission techniques. Recent extensions of cell-phone networks in all the project countries make it possible to communicate between field and office using SMS Field workers can send latest information on plant disease outbreaks and availability of disease-resistant cuttings Pictures of diseased plants can be taken and sent by cellphone for rapid disease identification A new generation of spatially aware smartphones/PDAs will be used for field data collection (Blackberry, HTC TyTnII). Data can be entered in Excel spreadsheets as it is collected in the field, and sent immediately to the office. GLCI staff in remote locations will be able to access latest information on the project through the web site, using smartphone technology

20. Training of project staff in the use of GPS and in basic GIS operations using freeware GIS software (DIVA) was an important part of C3P. Training manuals and course-books were developed in French and English for GPS and DIVA This will continue to be important in GLCI, and will be extended to staff from partner organisations involved in field implementation of the project. Trainers will be identified in each language zone, and will continue GPS and GIS training as required through the life of the project It is hoped that GLCI will not only contribute to greatly improved food security in the Great Lakes region, but will also contribute to capacity building in GPS, GIS and communication technologies.

21. GPS training in the field and at the computer during courses organised by C3P in Kenya and Congo

22. GIS training for project staff and partners was undertaken in French and English by C3P Free software (DIVA-GIS) was introduced to allow for simple and legal dissemination within the project

23. GIS-based modelling of the spread of CMD and CSBD could greatly assist cost-effective control of the impacts of these cassava diseases. Areas at greatest risk to future infection could be identified and planted pre-emptively with resistant varieties Better quantitative data on climatic and soil requirements of different resistant cassava varieties is needed in order to identify the best varieties for planting within this very diverse region END